Difference between revisions of "Manuals/calci/CORREL"

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==Examples==
 
==Examples==
  
#1. Find the correlation coefficients for X and Y values are given below :
+
#1. Find the correlation coefficients for X and Y values are given below :X={1,2,3,4,5};  Y={11,22,34,43,56}
X={1,2,3,4,5};  Y={11,22,34,43,56}
 
 
CORREL(A4:A8,B4:B8)=0.99890610723867
 
CORREL(A4:A8,B4:B8)=0.99890610723867
#The following table gives the math scores and times taken to run 100 m for 10 friends:
+
#The following table gives the math scores and times taken to run 100 m for 10 friends:SCORE(X)={52,25,35,90,76,40}; TIME TAKEN(Y)={11.3,12.9,11.9,10.2,11.1,12.5}CORREL(A5:A10,B5:B10)= -0.93626409417769
SCORE(X)={52,25,35,90,76,40}; TIME TAKEN(Y)={11.3,12.9,11.9,10.2,11.1,12.5}
+
#Find the correlation coefficients for X and Y values are given below :X={-4,11,34,87};Y={9,2,59,24} CORREL(A1:A4,B1:B4)=0.353184665607273
CORREL(A5:A10,B5:B10)= -0.93626409417769
 
#Find the correlation coefficients for X and Y values are given below :
 
X={-4,11,34,87};Y={9,2,59,24}
 
CORREL(A1:A4,B1:B4)=0.353184665607273
 
  
 
==See Also==
 
==See Also==

Revision as of 06:15, 9 December 2013

CORREL(ar1,ar2)


  • are the set of values.

Description

  • This function gives the correlation coefficient of the 1st set(ar1) of values and 2nd set(ar2) of values.
  • Correlation is a statistical technique which shows the relation of strongly paired variables.
  • For example ,test average and study time are related;those who spending time more to study they will get high marks and spending less time for studies their Average will goes down.
  • There are different correlation techniques measuring the degree of correlation.
  • The most common of these is the Pearson correlation coefficient denoted by r xy.
  • The main result of a correlation is called the correlation coefficient (or "r")which ranges from -1 to +1.
  • The r value is positive i.e.+1 when the two set values increase together then it is the perfect positive correlation.
  • The r value is negative i.e. (-1) when one value decreases as the other increases then it is called negative correlation.
  • Suppose the r value is 0 then there is no correlation (the values don't seem linked at all).
  • If we have a series of n measurements of X and Y written as xi and yi where i = 1, 2, ..., n, then the sample *correlation coefficient is: CORREL(X,Y)= r xy=[ summation(i=1 to n)(xi-x(bar))(yi-y(bar))]/ SQRT{ summation(i=1 to n)(xi-x(bar))^2 summation(i=1 to n)(yi-y(bar))^2], where x(bar) and y(bar) are the sample means of X and Y. *This function will give the result as error when
  1. ar1 and ar2 are nonnumeric or different number of data points.
  2. ar1 or ar2 is empty
  3. The denominator value is zero.
  • Suppose ar1 and ar2 contains any text, logical values, or empty cells, like that values are ignored.

Examples

  1. 1. Find the correlation coefficients for X and Y values are given below :X={1,2,3,4,5}; Y={11,22,34,43,56}

CORREL(A4:A8,B4:B8)=0.99890610723867

  1. The following table gives the math scores and times taken to run 100 m for 10 friends:SCORE(X)={52,25,35,90,76,40}; TIME TAKEN(Y)={11.3,12.9,11.9,10.2,11.1,12.5}CORREL(A5:A10,B5:B10)= -0.93626409417769
  2. Find the correlation coefficients for X and Y values are given below :X={-4,11,34,87};Y={9,2,59,24} CORREL(A1:A4,B1:B4)=0.353184665607273

See Also


References

Bessel Function